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Brian M Schilder, PhD
Passionately pursuing transdisciplinary research to advance human health and knowledge.
Postdoctoral Research Scientist
Below are selected subsets of the full CV. -
Education
Imperial College London / The Alan Turing Institute
PhD; Computational Genomics & Machine Learning
2024
Thesis: Multi-omic medicine: dissecting the cell type-specific and pleiotropic mechanisms underlying disease genomics at scale
The George Washington University / Georgetown University
MPhil; Comparative Neuroscience & Genomics
2017
Thesis: The evolution of the hippocampus and adult neurogenesis: novel insights into the origins of human memory
Brown University / Princeton University
ScB; Neurological Diseases & Disorders
2011
Core Skills
Research
15+ years of deep expertise in genomics, AI, evolutionary biology and biomedicine. Strategically fuses concepts and methods across multiple domains.
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- Publication record: 23 publications, 8 preprints and 13 awarded grants.
- Reproducibility: Global leader in promoting and enabling reproducible scientific practices. Writes 100% reproducible manuscripts programmatically.
- Bioinformatics: Created 45 Python and R packages to address key challenges in biological research.
- High-performance computing: Highly parallelised analyses and AI model training (CPUs and GPUs).
- Web development: 6+ websites, web apps, and interactive reports.
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AI & Machine Learning
Proficient in developing and deploying AI/ML models (PyTorch, tensorflow, Keras, sklearn and H2O) to solve complex biological problems. Applied examples include:
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- Causal variant effect prediction: Used functional impact predictions from DNA sequence models (DeepSEA, Basenji, IMPACT) to validate SNPs prioritised with Bayesian fine-mapping.
- Foundation models: Used transformer trained on >36M cells and protein sequence embeddings to uncover cell type-specific mechanisms of disease.
- LLM knowledge extraction: Developed framework to extract quantitative metrics of phenotype severity from GPT-4.
- Disease genomics embeddings: Developed VAE/graph models to reveal joint latent representation of genomic signatures across all diseases and phenotypes.
- NLP: Created a suite of proprietary Python packages for advanced topic modelling of the PubMed literature to provide business intelligence to the world’s largest digital health, biotech, and pharma companies (as a consultant with 120/80 Group).
- Tensor decomposition: Applied multi-condition factorisation to efficiently discover neurodegeneration-relevant trans-eQTLs
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Project Management
Efficient management strategies to define objectives, track progress and coordinate diverse teams.
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- Documentation: Defines objectives and tracks progress with GitHub Projects. Includes useful documentation in Issues, inline code and shareable reports.
- Version control: Extensive and daily use of GitHub, containers (Docker, Singularity, virtual machines), environments (conda) and pipelines (Nextflow).
- Team management: Led numerous collaborative research projects and supervised researchers at various career stages.
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Soft Skills
Advances science through effective problem formulation, collaboration and communication.
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- Problem formulation: Rapid hypothesis generation, project design, and creative problem solving.
- Collaboration: Diverse and global collaborative networking.
- Communication: Clear and concise distillation of complex results to a variety of audiences. Presented 25 conference posters.
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Publications
rworkflows: automating reproducible practices for the R community
Nature Communications (2023) 15(149); https://doi.org/10.1038/s41467-023-44484-5
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2023
BM Schilder, AE Murphy, NG Skene
News
- Featured in Nature Communications Editors’ Highlights
Artificial intelligence for neurodegenerative experimental models
Alzheimer’s & Dementia (2023) http://doi.org/10.1002/alz.13479
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2023
SJ Marzi, BM Schilder, A Nott, C Sala Frigerio, S Willaime-Morawek, M Bucholc, DP Hanger,C James, PA Lewis, I Lourida, W Noble, F Rodriguez-Algarra, JA Sharif, M Tsalenchuk, LM Winchester, U Yaman, Z Yao, DEMON Network, JM Ranson, DJ Llewellyn
Artificial intelligence for dementia genetics and omics
Alzheimer’s & Dementia (2023) http://doi.org/10.1002/alz.13427
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2023
C Bettencourt, NG Skene, S Bandres-Ciga, E Anderson, LM Winchester, IF Foote, J Schwartzentruber, JA Botia, M Nalls, A Singleton, BM Schilder, J Humphrey, SJ Marzi, CE Toomey, A Al Kleifat, EL Harshfield, V Garfield, C Sandor, S Keat, S Tamburin, C Sala Frigerio, I Lourida, DEMON Network, JM Ranson, DJ Llewellyn
Artificial intelligence for dementia research methods optimization
Alzheimer’s & Dementia (2023) http://doi.org/10.1002/alz.13441
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2023
M Bucholc, C James, A Al Khleifat, A Badhwar, N Clarke, A Dehsarvi, CR Madan, SJ Marzi, C Shand, BM Schilder, S Tamburin, HM Tantiangco, I Lourida, DJ Llewellyn, JM Ranson
EpiCompare: R package for the comparison and quality control of epigenomic peak files
Bioinformatics Advances (2023) 13(1):vbad049; https://doi.org/10.1093/bioadv/vbad049
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2023
S Choi, BM Schilder, L Abbasova, AE Murphy, NG Skene
Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies
Nature Genetics (2022) https://doi.org/10.1038/s41588-021-00976-y
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2022
K de Paiva Lopes, G JL Snijders, J Humphrey, A Allan, M Sneeboer, E Navarro, BM Schilder…T Raj
News
- Microglial transcriptomics meets genetics: new disease leads (Nature Reviews Neurology, 2022)
- Mighty MiGA: Microglial Genomic Atlas Zeros in on Causal AD Risk Variants (ALZFORUM, 2022)
- Can a Human Microglial Atlas Guide Brain Disorder Research? (Mount Sinai Health System, 2022)
- Polygenic Scores Paint Microglia as Culprits in Alzheimer’s (ALZFORUM, 2021)
Multi-omic insights into Parkinson’s Disease: From genetic associations to functional mechanisms
Neurobiology of Disease (2021) 105580; https://doi.org/10.1016/j.nbd.2021.105580
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2021
BM Schilder, E Navarro, T Raj
Fine-Mapping of Parkinson’s Disease Susceptibility Loci Identifies Putative Causal Variants
Human Molecular Genetics (2021) ddab294; https://doi.org/10.1093/hmg/ddab294
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2021
BM Schilder, T Raj
echolocatoR: An Automated End-to-End Statistical and Functional Genomic Fine-Mapping Pipeline
Bioinformatics (2021) btab658; https://doi.org/10.1093/bioinformatics/btab658
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2021
BM Schilder, J Humphrey, T Raj
MungeSumstats: A Bioconductor Package for the Standardisation and Quality Control of Many GWAS Summary Statistics
Bioinformatics (2021) 37(23):4593-4596; https://doi.org/10.1093/bioinformatics/btab665
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2021
A Murphy, BM Schilder, NG Skene
Dysregulation of mitochondrial and proteo-lysosomal genes in Parkinson’s disease myeloid cells
Nature Genetics (2021) https://doi.org/10.1101/2020.07.20.212407
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2021
E Navarro, E Udine, K de Paiva Lopes, M Parks, G Riboldi, BM Schilder…T Raj
News
- Mount Sinai: Fighting Neurodegenerative Disorders (Mount Sinai Health System, 2019)
Phenome-wide and eQTL Associations of COVID-19 Genetic Risk Loci
iScience (2021) https://doi.org/10.1016/j.isci.2021.102550
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2021
C Moon, BM Schilder, T Raj, K-l Huang
Genome-Wide Association Study of over 40,000 Bipolar Disorder Cases Provides Novel Biological Insights
Nature Genetics (2021) 53:817-829; https://doi.org/10.1038/s41588-021-00857-4
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2021
N Mullins, AJ Forstner, KS O’Connell, B Coombes, JRI Coleman…BM Schilder… et al.
News
- Researchers identify 64 regions of the genome that increase risk for bipolar disorder (EurekAlert, 2021)
- Largest Bipolar Disorder Genetics Study Doubles Genetic Risk Factors (Nordic Society of Human Genetics and Precision Medicine, 2021)
Tensor decomposition of stimulated monocyte and macrophage gene expression profiles identifies neurodegenerative disease-specific trans-eQTLs
PLOS Genetics (2020) 16(9):e1008549; https://doi.org/10.1371/journal.pgen.1008549
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2020
S Ramdhani, E Navarro, E Udine, AG Efthymiou, BM Schilder, M Parks, A Goate, T Raj
Evolutionary shifts dramatically reorganized the human hippocampal complex
Journal of Comparative Neurology (2019) 528(17):3143-3170; https://doi.org/10.1002/cne.24822
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2019
BM Schilder, HM Petry, PR Hof
FAIRshake: Toolkit to Evaluate the Findability, Accessibility, Interoperability, and Reusability of Research Digital Resources
Cell Systems (2019) 9; https://doi.org/10.1016/j.cels.2019.09.011
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2019
D Clarke, L Wang, A Jones, M Wojciechowicz, D Torre, K Jagodnik, S Jenkins, P McQuilton, Z Flamholz, M Silverstein, BM Schilder…A Ma’ayan
News
- Chosen as ‘Featured Frontmatter’ article in Cell Systems
Geneshot: search engine for ranking genes from arbitrary text queries
Nucleic Acids Research (2019) 47(W1):W571-W577; https://doi.org/10.1093/nar/gkz393
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2019
A Lachmann, BM Schilder, ML Wojciechowicz, D Torre, MV Kuleshov, AB Keenan, A Ma’ayan
News
- Geneshot: Piercing the Literature to Identify and Predict Relevant Genes (University of Pittsburgh Health Sciences Library System Update, 2019)
- The Future of AI at the Hasso Plattner Institute for Digital Health at Mount Sinai (Mount Sinai Health System, 2020)
eXpression2Kinases (X2K) Web: linking expression signatures to upstream cell signaling networks
Nucleic Acids Research (2018) 46(W1):W171-W179; https://doi.org/10.1093/nar/gky458
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2018
DJB Clarke, MV Kuleshov, BM Schilder, D Torre, ME Duffy, AB Keenan, A Lachmann, AS Feldmann, GW Gundersen, MC Silverstein, Z Wang
News
- Mount Sinai Faculty Spotlight: Ma’ayan Lab (Mount Sinai Health System, 2018)
Defining elemental imitation mechanisms: A comparison of cognitive and motor-spatial imitation learning across object- and computer-based tasks
Journal of Cognition and Development (2015) 17(2):221-243; https://doi.org/10.1080/15248372.2015.1053483
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2015
F Subiaul, L Zimmerman, E Renner, BM Schilder, R Barr
Take the monkey and run
Journal of Neuroscience Methods (2015) 248:28-31; http://doi.org/10.1016/j.jneumeth.2015.03.023
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2015
KA Phillips, MK Hambright, K Hewes, BM Schilder, CN Ross, SD Tardif
News
- Monkeys on a Treadmill? A Conversation with Dr. Kimberley Phillips (Why Social Science?)
Working memory constraints on imitation and emulation
Journal of Experimental Child Psychology (2014) 128:190-200; http://doi.org/10.1016/j.jecp.2014.07.005
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2014
F Subiaul, BM Schilder
Preprints
Zero-shot transfer learning of genomic disease signatures using single-cell foundation models
arXiv (2024)
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2024
BM Schilder
Harnessing generative AI to annotate the severity of all phenotypic abnormalities within the Human Phenotype Ontology
medRxiv (2024) https://doi.org/10.1101/2024.06.10.24308475
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2024
KB Murphy, BM Schilder, NG Skene
Chromatin interactions and active histone mark signatures underpin TBXT expression in metastatic lung cancer
SSRN (2024) https://ssrn.com/abstract=4965385
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2024
RM Yaa, BM Schilder, RD Acemel, FC Wardle
Integrative multi-omics analysis of glial signatures associated with accelerated cognitive decline in Alzheimer’s disease
bioRxiv (2024)
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2024
E Schneegans, N Fancy, V Chau, TKD Cheung, E Adair, M Papageorgopoulou, BM Schilder, PM Matthews, JS Jackson
Fine-mapping genomic loci refines bipolar disorder risk genes
medRxiv (2023) https://www.medrxiv.org/content/10.1101/2024.02.12.24302716v1
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2023
M Koromina, A Ravi, G Panagiotaropoulou, BM Schilder, … S Ripke, T Raj, JRI Coleman, N Mullins
News
- Currently under journal review
Identification of cell type-specific gene targets underlying thousands of rare diseases and subtraits
medRxiv (2023) https://doi.org/10.1101/2023.02.13.23285820
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2023
KB Murphy, R Gordon-Smith, J Chapman, M Otani, BM Schilder, NG Skene
CUT&Tag recovers up to half of ENCODE ChIP-seq peaks
bioRxiv (2022) https://doi.org/10.1101/2022.03.30.486382
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2022
D Hu, L Abbasova, BM Schilder, A Nott, NG Skene, SJ Marzi
Research Experience
Postdoctoral Research Scientist
Cold Spring Harbor Laboratory (Quantitative Biology)
- - 2024
- Advancing deep learning applications in genomics and biomedicine in the laboratory of Dr. Peter Koo.
- Developing a genomic foundation model to map complex genome-phenome relationships and make highly accurate, personalized disease risk predictions.
Lead Data Scientist
120/80 Group
- - 2019
- Offers data-driven consultation services to a wide portfolio of high-profile digital healthcare, pharmaceutical and biotech companies.
- Developed a suite of proprietary softwares to extract customised business intelligence from the published literature to generate customised and interpretable reports to clients.
- Provides clients guidance on strategic AI implementation, data analysis, publication and transparency.
Bioinformatician II
Icahn School of Medicine at Mount Sinai (Department of Neuroscience / Department of Neurology / Department of Genetics & Genomics / Ronald M. Loeb Center for Alzheimer’s Disease)
2020 - 2018
- Developed machine learning systems to integrate large-scale multi-omics datasets (e.g. whole-genome sequencing, bulk and single-cell RNA-seq, epigenomics, clinical data) to uncover the molecular mechanisms underlying neurodegenerative diseases (e.g. Alzheimer’s, Parkinson’s, ALS).
- Computationally identified specific disease-causal variants, pathways and cell-types for subsequent functional wet lab validation (e.g. CRISPR-cas9 editing in patient-derived cell cultures, iPSCs and cerebral organoids).
Bioinformatician II
Icahn School of Medicine at Mount Sinai (Department of Pharmacological Sciences)
2018 - 2017
- Conducted computational systems biology research. Integrated and analyzed large-scale genomic and biomedical data (e.g. Python, R, JavaScript).
- Developed evolutionary algorithm to optimize gene network kinase regulator prediction (eXpression2Kinases).
- Developed and deployed computational tools, software, databases and web applications for basic and clinical research, resulting in 3 peer-reviewed publications.
Research Assistant
The George Washington University (Department of Anthropology)
2013 - 2011
- Performed dissection, histology, microscopy and quantitative stereology in post-mortem primate brain tissues.
- Trained junior and senior personnel on lab protocols.
Senior Lab Manager
The George Washington University (Department of Speech, Language & Hearing Sciences)
2013 - 2011
- Organized and trained dozens of undergraduates to conduct weekly cognitive development research; designed and/or directly contributed to over 15 research projects in two years.
Paid Research Intern
Princeton University (Princeton Neuroscience Institute)
2010
- Investigated the neural basis of decision-making in humans.
- Recruited participants, recorded EEG and analyzed data in MATLAB.
Grants
Total (all grants): $2,949,872
Total (as primary applicant): $311,382
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